This component of the PPG is dedicated to quantitative, structural, and computational modeling aspects of our collaborative effort to understand the mechanisms of hallucinogenic drugs in various tructural classes, triggered by their interactions with the subtypes of 5-HT GPCRs. The aim to understand the mechanisms that engender the complex behavioral effects in hallucinogenesis, is based on the hypothesis that the hallucinogenic potential of certain compounds results from specific modes of interaction with these receptors, that produce distinct molecular signaling mechanisms; thus, hallucinogens trigger structural and dynamic receptor responses (affecting protein-protein interactions) that differ from those produced by other ligands. This hypothesis leads to proposed investigations of (i) the modes of receptor response (conformational rearrangements and stabilization of "activated state(s)") that trigger special protein-protein interactions ranging from receptor oligomerization to interactions with various scaffolding proteins (e.g., PDZ- BAR-domains), and (ii) how such conformational rearrangements and resulting association/dissociation of protein- protein interactions affect selectivity and efficiency in the signaling pathways of hallucinogens. We develop and apply computational methods, modeling and simulation approaches (from structural biophysics, bioinformatics, predictive mathematical modeling) to study molecular and cellular signaling systems involved in the mechanisms. The studies are closely coordinated with Projects 2 and 3 of the PPG in which probing and validation of the models will be based on collaboratively designed experiments utilizing inferences, designs and protein constructs investigated in this project. These collaborative studies will serve to incorporate the structural context of molecular interactions in systems level models of the hallucinogen signaling mechanisms. The components of a hallucinogen signaling map will be stored in an information management system (SigPath) ultimately used to model quantitatively the pathways and learn about their characteristic properties, and their integration in the cellular machinery. We plan to start with modest, scientifically responsible simulations of small pathway elements in order to support hypothesis testing and design of experiments in the PPG that explore such pathways.